A quantitative assessment of fish passage efficiency
Michael J Noonan, James W A Grant & Christopher D Jackson
Department of Biology, Concordia University, 7141 Sherbrooke Street West, Montreal,
QC, Canada, H4B 1R6,
Correspondence:
Michael J Noonan, Department of Biology, Concordia University, 7141 Sherbrooke
Street West, Montreal, QC, Canada, H4B 1R6
Tel.: (514) 848 2424 Ext. 4027
Fax: (514) 848 2424 Ext. 2881
E-mail: m_noona@live.concordia.ca
Alternate Titles
Assessing the effectiveness of fishways and other passage facilities
Assessing the current state of fishways and other passage facilities
Running Title
Effectiveness of fish passage facilities
Main Text
Abstract
In an attempt to restore the connectivity of fragmented river habitats, a variety of passage
facilities have been installed at river barriers. Despite the cost of building these structures,
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there has been no quantitative evaluation of their overall success at restoring fish passage.
We reviewed articles from 1960 to 2011, extracted data from 65 papers on fish passage
efficiency, size and species of fish, and fishway characteristics to determine the best
predictors of fishway efficiency. Because data were scarce for fishes other than
salmonids (order Salmoniformes), we combined data for all non-salmonids for our
analysis. On average, downstream passage efficiency was 68.5%, slightly higher than
upstream passage efficiency of 41.7%, and neither differed across the geographical
regions of study. Salmonids were more successful than non-salmonids in passing
upstream (61.7 versus 21.1%) and downstream (74.6 versus 39.6%) through fish passage
facilities. Passage efficiency differed significantly between types of fishways; pool &
weir, pool & slot, and natural fishways had the highest efficiencies, whereas Denil and
fish locks/elevators had the lowest. Upstream passage efficiency decreased significantly
with fishway slope, but increased with fishway length, and water velocity. An
information theoretic analysis indicated that the best predictors of fish passage efficiency
were order of fish (i.e. salmonids > non-salmonids), type of fishway, and length of
fishway. Overall, the low efficiency of passage facilities indicated that most need to be
improved to sufficiently mitigate habitat fragmentation for the complete fish community
across a range of environmental conditions.
Keywords Conservation, dams, fishways, habitat fragmentation, migration, passage
efficiency
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________________________________________________________________________
Introduction
Methods
Literature search
Data analysis
Statistical analysis
Results
Discussion
Acknowledgements
References
________________________________________________________________________
Introduction
Habitat loss and fragmentation are the major threats to both terrestrial and aquatic
biodiversity, including freshwater fishes (Andrén 1994; Fahrig 1997; Larinier 2001).
Given the linear nature of freshwater habitats, dams and weirs act as anthropogenic
barriers that fragment the river, obstructing the movement of organisms and nutrients,
and reducing the amount of available habitat for fishes (Poff and Hart 2002; Sheer and
Steel 2006). Indeed, more than half of the world’s largest river systems are currently
negatively affected by dams (Nilsson et al. 2005). These barriers have frequently been
implicated in the decline of resident and anadromous fish populations due to their
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negative effects on upstream adult migration (Caudil et al. 2007) and downstream
migration by juveniles and adults
(Wertheimer and Evans 2005; Arnekleiv et al. 2007). Indeed, habitat loss is the most
important threat to endangered freshwater fishes in Canada, and infrastructure such as
dams and impoundments are the most important human activity causing the loss of
habitat (Venter et al. 2006).
Even when upstream passage has been satisfactory, other negative effects of dams
include a delay in migration in a wide variety of fish species (Haro and Kynard 1997;
Lucas and Frear 1997; Moser et al. 2000, 2002; Karppinen et al. 2002; Keefer et al. 2004;
Zigler et al. 2004; Hasler et al. 2011)(, higher energetic expenditures during migration
(Tiffan et al. 2010), and a failure to reach the spawing grounds (Gowan et al. 2003).
In an attempt to counteract the negative effects of habitat fragmentation, a wide
variety of devices have been installed at river barriers to restore connectivity, and aid
with both upstream and downstream fish migration (Clay 1995). Two of the most
common devices to assist upstream migration are fishways, structures that allow fish to
swim upstream under their own effort, and fish locks/elevators, devices that lift the fish
over obstructions (Clay 1995). Downstream devices include physical screens, angled bar
racks, and surface bypasses, intended to divert juveniles from passing downstream via the
turbines (Larinier 2001). The design of these fishways and lifts has largely focused on
economically important, anadromous species, and as a result many non-target species are
not able to fully ascend the structure (Office of Technology Assessment 1995). Even well
designed facilities will vary in their effectiveness depending on inter-individual
differences in in swimming behaviour (Hinch and Bratty 2000; Castro-Santos 2005, and
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physiological condition of the fish (Pon et al. 2009; Hasler et al. 2011). In addition, a
large number of fishways still prevent or delay the migration of target species (Gowans et
al. 2003; Boggs et al. 2004a & 2004b; Keefer et al. 2004) due to the lack of sufficient
flow to attract fish to the entrance (hereafter, attraction flow), unsuitable entrance
location, inadequate maintenance, and/or poor hydraulic conditions, which are not
designed to aid the target species (Larinier 2001). Therefore, the presence of a fishway
may not fully mitigate the fragmentation induced by a river barrier (Roscoe and Hinch
2010).
Evaluating a fishway’s efficiency after construction is crucial to ensure the
structure is serving its purpose, and to make necessary adjustments (Clay 1995; Roscoe
and Hinch 2010). Numerous summaries on how to design an effective fishway exist (e.g.
Clay 1995; Odeh 1999; Larinier 2002), but there has only been one qualitative analysis of
the effectiveness of fishways (Roscoe and Hinch 2010). Roscoe and Hinch (2010)
identified the major questions addressed concerning fishway design, including the
efficiency with which individuals were able to pass a fishway, as well as the biological,
environmental, or structural mechanisms affecting passage. In addition, they described
trends in fishway publications and concluded that the focus of research has not changed
significantly over time. The purpose of our study was to complement their analysis by
quantifying the efficiency of fishways at providing upstream and downstream passage for
fishes. Specifically, we quantified the passage efficiency of different species and sizes of
fish in relation to the type of passage facility and its specific design characteristics,
including its height, gradient, length, and water velocity through the structure.
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Methods
Literature search
An extensive literature search for articles using the search terms ‘fishway’, ‘fishpass’,
‘fish bypass’, ‘fish’, ‘dam’ and ‘passage’ was previously conducted by Roscoe and Hinch
(2010) via the ISI Web of Knowledge, and Aquatic Sciences and Fisheries Abstracts (for
more details see Roscoe and Hinch 2010). The 96 peer-reviewed articles identified by
their search criteria were used for this study, supplemented with 26 articles published
since June 2008, obtained using the same search terms and the ISI Web of Knowledge.
These articles encompassed both up- and downstream movement of fish through
dedicated passage facilities across 61 dams/obstructions found in 20 countries from North
America (30 dams/obstructions), Europe (24 dams/obstructions), South America (3
dams/obstructions), and Australia (4 dams/obstructions) (see references with asterisks).
Included were articles from 1964 to 1 January 2011.
For each study, we recorded the following information, when available: migration
direction, river, dam/obstruction of study, fishway type (see below), technical
characteristics of the fishway, including length, width, height, mean water depth, slope,
and mean water velocity of the fishway, sample size (i.e. number of fish), and mean
length of all fishes recorded in the study. While it is clear that hydraulic characteristics
vary markedly within a fish passage facility (e.g. Hinch and Bratty 2000), detailed
information was unavailable for most facilities. These values were compared against the
species, life-stage, migration time, attraction, entrance, and passage efficiencies, fallback
percentage, and passage times of their respective studies. For the purpose of this study,
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attraction efficiency was defined as the percentage of potential migrants that was able to
locate the fishway entrance (Aarestrup et al. 2003), whereas entrance efficiency was the
percentage at the fishway entrance, that enter a fishway (Evans et al. 2008). Passage
efficiency was defined as the percentage of fish present which entered, and successfully
moved through a fishway (Larinier 2001) and encompassed both attraction and entrance
efficiency. Passage time was defined as the time elapsed since first detection within the
vicinity of the tailraces of a dam to the moment of successful fishway exit (Caudill et al.
2007). Fallback was defined as the percentage of fish that pass back downstream via
spillways, turbine intakes, or other means, after the successful ascension of a fishway
(Boggs et al. 2004).
Data analysis
To avoid the overrepresentation of studies with a large amount of data, or of highly
studied dams, one data point per facility, per study was recorded. If a particular study had
multiple data points for a single facility, a weighted average was recorded. In the case of
cross study comparisons of a single facility, the median value for the facility was used as
a datum in our analysis. In a few cases, efficiency values were reported as being less than
zero or greater than one hundred. In these cases the values were adjusted to zero and one
hundred percent, respectively. When sample sizes permitted, further analyses were
conducted to determine if order of fish (see below), diel differences, geographical
location, fishway type, as well as the technical characteristics of a fishway affected
fishway efficiency. When a study reported data on the passage efficiency of several
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species, one data point per species was used to evaluate the effect of fish size on passage
efficiency. Fork length was converted to total length using species-specific conversion
factors (www.fishbase.org).
We first grouped fish by family and order for statistical analysis. Because data
were scarce for all orders except for salmonids (Salmoniformes), we divided all fish into
two groups: salmonids and non-salmonids. While this division is clearly arbitrary, it was
useful because salmonids have higher swimming speeds than other fishes (Webb 1975),
and many fishways are designed specifically for economically important salmonid
species (Larinier 2001). When a study reported a significant difference in the time of day
during which a species used a fishway, the preferred time of passage was recorded.
Following Roscoe and Hinch (2010) we divided the studies into three geographical
locations: North America, Europe and Australia/South America.
Fish passage facilities designed for upstream passage were grouped into five
categories: pool and weir, pool and slot, natural, Denil, fish lift/lock, and trap and truck.
Pool and weir fishways were constructed as a series of small pools in steps, and required
fish to swim over dividers from pool to pool (Clay 1995). Pool and slot fishways were
constructed as a series of small pools in steps with openings that allowed fish to swim
through dividers between pools (Clay 1995). Fishways built to resemble a natural
channel, with suitable substrate, water flows, morphology, and slopes, were categorized
as natural fishways (Calles and Greenberg 2005). Denil fishways included those designed
as a steep flume with vanes installed to dissipate the flow and decrease velocity (Clay
1995). Fish lift/lock systems collected fish in an enclosed lock and then raised the water
level to the top of the dam by the addition of water (Zilukas and Ziliukiene 2002). Trap
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and truck installations included some form of attraction/collection system, followed by
the transportation of collected fish upstream via appropriate vehicles (Schilt 2007). If a
structure contained a combination of fishway types, or the types were not explicitly stated
in the article, they were excluded from analyses of efficiency vs. type of fishway.
Statistical analysis
We could not conduct a formal meta-analysis because most studies reported the
percentage of fish passing successfully through a facility without an estimate of variance
(see Harrison 2011). We used analyses of variance (ANOVA), covariance (ANCOVA),
Pearson’s correlations and Sign tests (=0.05) in an initial descriptive analysis of the
data. The efficiency values were subjected to angular transformations for all statistical
analyses. We then used an information theoretic approach (Burnham et al. 2010), using
Akaike’s information criterion adjusted for small sample sizes (AICc) to identify the
model that best explained the observed upstream passage efficiencies. Although statistical
analyses were performed on transformed data, for visual purposes, we used the
untransformed data in all figures.
Results
Data were scarce for fishes other than salmonids (Table 1). Hence, we first analyzed
upstream passage efficiency for all non-salmonid orders, including estimates for complete
fish communities (Fig. 1). Because the mean upstream passage efficiency for non-
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salmonid orders did not differ significantly (F[4,35]=0.554, P=0.697), we combined the
data for all non-salmonids in subsequent analyses.
Mean passage efficiency did not differ significantly between upstream (x̄ =41.7%,
SE=4.4, n=61) and downstream (x̄ =68.5%, SE=6.4, n=17) directions (two-way ANOVA:
F[1,74]=3.07, P=0.084), but was higher for salmonids (downstream: x̄ =74.6%, SE=6.4,
n=14; upstream: x̄ =61.7%, SE=5.9, n=31) than non-salmonids (downstream: x̄ =39.6%,
SE=10.7, n=3; upstream: x̄ =21.1%, SE=3.7, n=30) (two-way ANOVA: F[1,74]=15.4,
P<0.0005) (Fig. 2). Upstream migrating salmonids used the fishways primarily during the
day in 16 of 17 studies (Sign test: P<0.0005), whereas non-salmonids showed no
preference (5 during the day vs. 5 at night; Sign test: P=1.00). Furthermore, upstream
passage efficiency did not differ significantly between continents (data not shown; twoway ANOVA: F[2,50]=0.50, P=0.608) but did differ significantly between salmonids and
non-salmonids (see below; two-way ANOVA: F[1,50]=11.31, P=0.002).
The type of fishway had a significant effect on passage efficiency (two-way
ANOVA: F[4,63]=4.781, P=0.002) (Fig. 3), as did order of fish (two-way ANOVA:
F[1,63]=13.496, P<0.0005), with salmonids having a higher efficiency than non-salmonids;
there was no significant interaction between species of fish and type of fishway (two-way
ANOVA: F[4,63]=0.445, P=0.776). Pool & weir fishways did not differ significantly from
pool & slot, or natural fishways (Tukey post hoc test, all P-values > 0.14), but had higher
passage efficiency than Denil fishways and fish locks/elevators (Tukey post hoc test, all
P-values <0.0005 respectively); no other comparisons differed significantly from one
another.
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Because fish locks/elevators differ fundamentally from the other types, in that
they do not require fish to swim upstream under their own effort (Clay 1995), they were
excluded from further analysis of the effects of technical characteristics. To determine
how pool & weir, pool & slot, natural, and Denil fishways differed, one-way ANOVAs
were used to compare three basic technical characteristics: length, slope, and velocity
(Table 2). Total fishway length differed significantly between types (F[3,25]=6.347,
P<0.0005), as did the slope (F[3,26]=12.279, P<0.0005) and water velocity (F[3,16]=4.091,
P=0.025). For all three characteristics, pool & weir, pool & slot, and natural fishways did
not differ significantly (Tukey post hoc test: all P-values > 0.086), but all three differed
significantly from Denil fishways (Tukey post hoc test: all P-values < 0.046), except for
water velocity between natural and Denil fishways (P=0.250) and length between pool &
slot and Denil fishways (P=0.234). Fishway slope was negatively correlated with fishway
length and velocity, whereas fishway length was positively correlated with velocity
(Table 2b).
For all fishways that required fish to swim upstream under their own effort,
upstream passage efficiency decreased as the slope increased (ANCOVA: F[1,34]=6.45,
P=0.016; Fig. 4a), increased with the length of the fishway (ANCOVA: F[1,38]=4.79,
P=0.035; Fig. 4b), and increased with the water velocity through the fishway (ANCOVA:
F[1,24]=6.47, P=0.018; Fig. 4c). In all cases, efficiency was higher for salmonids than nonsalmonids (fishway length: ANCOVA, F[1,34]=12.34, P=0.001; slope: ANCOVA,
F[1,38]=6.01, P=0.019; water velocity: ANCOVA, F[1,24]=4.17, P=0.052). Upstream
passage efficiency also increased with total fish length for salmonids (Pearson’s
correlation: r=0.737, n=19, P<0.0005), but not for non-salmonids (Pearson’s correlation:
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r=0.092, n=17, P=0.724, Fig. 4d). Species of salmonid was not related to passage
efficiency once fish length was included in the model (ANCOVA: F[7,10]=0.87, P=0.56).
Total fish length was not significantly related to downstream passage efficiency for
salmonids (Pearson’s correlation: r=-0.321, n=9, P=0.400) and there was insufficient data
(n=1) to analyze the non-salmonids.
Passage time differed significantly between orders of fish (one-way ANOVA:
F[1,15]=46.353, P<0.0005), and was longer for non-salmonids (x̄ =5.52 days, SE=1.61,
n=3) than for salmonids (x̄ =0.87 days, SE=0.10, n=14). However, fallback after
successful upstream passage did not differ significantly between salmonid species(oneway ANOVA: F[3,26]=0.80, P=0.505) (Fig. 5).
Mean attraction efficiency (x̄ =65.1%, SE=7.6, n=12) was significantly higher
than entrance efficiency (x̄ =39.6%, SE=8.1, n=11) (one-way ANOVA: F[1,21]=5.60,
P=0.028), but there was insufficient data to perform any further statistical analysis on
species-specific trends. Attraction and entrance efficiency were negatively related to the
slope of the fishway, (ANCOVA: F[1,13]=5.48, P=0.036, Fig. 6a), and positively, but not
significantly, related to the length of the fishway (ANCOVA: F[1,16]=2.345, P=0.145,
Fig. 6b). In both cases, attraction efficiency was higher than entrance efficiency
(ANCOVA: F[1,13]=9.99, p=0.008; F[1,16]=8.13, P=0.012, respectively). There was
insufficient data to study the effects of water velocity on attraction and/or entrance
efficiency (n=4, and 3, respectively).
To determine the best predictors of fish passage efficiency, we used an
information-theoretic approach (Burnham et al. 2010) to select the best model. Of the
models analysed using the complete data set, three had AICc values within 2 of the best
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model (Table 3a). However, the only single-factor model in this group included order of
fish (i.e. salmonids versus non-salmonids) as the best predictor of upstream passage
efficiency (Table 3a). Type of fishway alone was not supported, however models that
included species and type were also well supported. In the reduced data set that included
technical characteristics of the fishway, three models emerged with AICc values within 2
of the best model. The only single factor model in this group included length of the
fishway as the best predictor of passage efficiency. However, models that also included
order of fish and type of fishway could not be ignored (Table 3b).
Discussion
To mitigate habitat fragmentation caused by anthropogenic barriers, upstream passage
facilities should allow 90-100% of migrating adult fish to pass in a safe and rapid manner
(Ferguson et al. 2002; Lucas and Baras 2001) . Our analysis indicated that the mean
upstream passage efficiency of only 41.7% was well below this desired goal. While many
studies reported passage efficiencies at facilities within the desired ranges, many more
reported much lower efficiencies, including several facilities with 0% passage efficiency
(Laine et al. 1998; Bunt et al. 2000; Knaepkens et al. 2006; Mallen-Cooper & Stuart
2007). Even though the average downstream passage efficiency of 68.5% was slightly
higher than upstream, it was clear that current fishways are not achieving their primary
conservation goal of restoring the connectivity of freshwater ecosystems.
Regardless of fishway type, salmonids were more successful than non-salmonids
at bypassing barriers. Indeed, order of fish was the best overall predictor of upstream
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passage efficiency in the complete data set, and was included in the best supported
models in the reduced data set. The relative success of salmonids is likely related to their
strong swimming ability (Webb 1975) and to the design of fishways, which often target
adults of commercially important species, such as anadromous salmonids (Larinier 2001;
Calles and Greenberg 2005; Parsley et al. 2007; Schilt 2007). For example, in the
Columbia and Snake Rivers, fishways are well designed for passing anadromous
salmonids, whereas non-salmonids are unable to use the fishways effectively (Moser et
al. 2002a,b). As the goal of conservation activities shifts from a maximum-sustainableyield to a biodiversity-protection approach, it will be increasingly important to consider
the swimming abilities and behaviour of the complete fish community (Oldani et al.
2007). Given this new conservation perspective, our analysis highlights the need for more
research on non-salmonid species.
Our results indicate that the type of fishway was an important parameter in most
well supported models predicting passage efficiency. Pool-type fishways had the highest
efficiency, followed closely by natural fishways, whereas fish locks/elevators and Denil
fishways were less efficient. When a reduced data set was analyzed, including the
characteristics of the three main types of fishways, fishway length was the best predictor
of upstream passage efficiency. Curiously, longer fishways had higher passage efficiency.
All else being equal, a longer fishway would increase the energy expenditure of the
migrating fish, and thus decrease passage efficiency. However, energy expenditure may
be more related to fishway steepness than length (Mallen-Cooper & Stuart 2007), and
fishway length and slope were negatively correlated. Hence, our findings were in
agreement with those showing that fish passage decreases with the slope of the fishway
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(Mallen-Cooper & Stuart 2007). The poor success of Denil fishways may be related to
the shortness (x̄ =14.2 m) and steepness (x̄ =14.5%) of these structures.
Water velocity through the fishway was positively correlated with upstream
passage efficiency, but too few data were available for further analyses. Although the
energy expenditure of migrating fish increases with swimming speed and water velocity
(Webb 1975), higher water velocities attract more fish to the fishway (Weaver 1963).
The inability of fish to locate fishway entrances results from the numerous sources of
water discharge in the dam tailrace, such as undesirable eddies, boils, and upwellings that
act as directional stimuli and confuse salmon (Clay 1995; Brown et al. 2006). While
fishways require a constant flow of water through their structure, resulting in lost
production of hydroelectric power, the loss is typically a fraction of the annual capital
cost of the fishway (see below; Clay 1995). Denil fishways also had the lowest mean
water velocities, likely resulting in poorer attraction of potential migrants.
Our findings may have implications for the assessment of infrastructure
development in countries with strict environmental policies. For example, in Canada the
Fisheries Act requires proponents of new projects to achieve ‘No Net Loss’ of the
productive capacity of habitats for fisheries (Quigley and Harper 2006). As such, the
construction of an effective passage facility may be required whenever a dam or barrier is
constructed. A free standing, concrete reinforced, pool-type fishway that takes no
advantage of natural contours costs about $2,600/m3 (2011 U.S. dollars), with annual
expenses of about 1-2% of the capital cost (Clay 1995). A fishway that can take
advantage of any natural contours will reduce these costs accordingly. Denil fishways,
often the cheapest option (Clay 1995), cost about $124,000 (2011 U.S. dollars) per
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vertical meter (Erkan 2002) with minimal maintenance and operation costs (Clay 1995).
Fish locks and elevators cost roughly $2.4 million (2011 U.S. dollars) to install, with
annual maintenance charges of 5% of the capital cost (Clay 1995). While Denil fishways
are generally the most economical option, they also had the lowest mean passage
efficiency, approximately 16%. Our analysis suggests that the more expensive pool and
natural fishways were also the most effective. However, only the very best designed
fishways are approaching 100% success, which would satisfy the ‘No Net Loss’ policy of
Canada. Indeed, the average fishway in our data set allowed only 62% of salmonids and
21% of non-salmonids to pass upstream. Application of the precautionary principle
would imply that the average barrier equipped with a fishway reduced the productive
capacity of the ecosystem by about 50%.
The design of a fishway is highly relevant to the efficiency of its performance,
affecting its use by fish, and the species that it may pass (Agostinho et al. 2002). Many
currently installed fishways have technical characteristics that are poorly matched to the
ichthyofauna present, exemplified by undesirably low mean passage efficiencies. These
characteristics need to be measured and reported more frequently, particularly in Canada
(see Hatry et al. in press), if we are to develop more effective fish passage facilities.
Acknowledgements
We thank the Natural Sciences and Engineering Council of Canada (NSERC) and
Concordia University for their support in the form of an NSERC Discovery grant to
J.W.A.G. and an NSERC Undergraduate Student Research Award to M.J.N. Dylan
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Fraser and two anonymous referees provided valuable feedback on an early version of the
manuscript and Robert Weladji assisted with the statistical analysis.
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33
Table 1 The taxonomic distribution of upstream and downstream passage efficiency data.
One datum was used per facility per family of fish , per study.
Family
Salmonidae
Entire Community
Order
Salmoniformes
-
N Upstream
N Downstream
31
14
9
-
Clupeidae
Clupeiformes
8
2
Percidae
Perciformes
6
-
Cyprinidae
Cypriniformes
6
-
Petromyzontidae
Petromyzontiformes
5
-
Catostomidae
Cypriniformes
3
-
Cottidae
Scorpaeniformes
3
-
Percichthyidae
Perciformes
3
-
Centrarchidae
Perciformes
2
-
Acipenseridae
Acipenseriformes
1
-
Esocidae
Esociformes
1
-
Lotidae
Gadiformes
1
-
Balitoridae
Cypriniformes
1
-
Cobitidae
Cypriniformes
1
-
Retropinnidae
Osmeriformes
1
-
Galaxiidae
Osmeriformes
1
-
Characidae
Characiformes
1
-
Anostomidae
Characiformes
1
-
Prochilodontidae
Characiformes
1
-
Loricariidae
Siluriformes
1
-
Terapontidae
Perciformes
1
-
34
Anguillidae
Anguilliformes
-
35
1
Table 2 (a) Mean values of the primary technical characteristics for four types of fish
passage facility, and (b) Pearson’s correlation coefficients (N) between the three
characteristics.
(a)
Type of
fishway
Length
(m)
SE
n
Slope
(%)
SE
n
Velocity
(m/s)
SE
n
Pool & weir
190.3
± 71.4
7
8.1
± 0.75
11
1.78
± 0.18
9
Pool & slot
175.6
± 101.8
5
6.3
± 2.42
3
2.07
± 0.33
3
Natural
202.9
± 41.4
10
4.2
± 1.11
9
1.80
± 0.50
2
14.2
± 5.3
8
14.5
± 1.47
10
0.89
± 0.21
7
Denil
(b)
Length (m)
Slope (%)
-0.703** (23)
Velocity (m/s)
-0.474 (13)
Velocity (m/s)
0.594* (13)
36
(a) Table 3 Model selection using Akaike’s information criterion adjusted for small
sample sizes (AICc) to assess variation in upstream passage efficiency using a)
the complete data set, and b) a reduced data set incorporating technical
characteristics of the fishway (length and slope). Order denotes salmoniformes vs.
all other orders, whereas type refers to pool & weir, pool & slot, natural, and
Denilfishways.
a) Complete Data Set n=47
AICc
∆i
Order
a
53.39
0.00
0.52632
Order + Type
55.04
1.65
0.23077
Order*Type
55.27
1.88
0.20580
Intercept
58.64
5.25
0.03816
Type
58.83
5.44
0.03474
b) Reduced Data Set n=26
AICc
∆i
Length + Order*Type
25.45
0.00
0.29175
Order*Type
26.26
0.81
0.19436
Order + Length
27.01
1.55
0.13405
Length
27.53
2.08
0.10300
Order + Type + Length
28.69
3.23
0.05787
Slope + Order*Type
28.84
3.39
0.05363
Length + Slope + Order*Type
29.12
3.67
0.04656
Type + Length
29.32
3.87
0.04211
Order + Type
30.87
5.42
0.01944
a
37
wi
wi
a
Order
31.89
6.44
0.01166
Type
32.12
6.67
0.01039
Order + Slope
32.32
6.86
0.00943
Slope
32.75
7.30
0.00757
Order + Type + Length + Slope
33.09
7.64
0.00641
Intercept
34.00
8.55
0.00406
Order + Type + Slope
34.11
8.66
0.00385
Type + Slope
34.36
8.91
0.00339
The selected model.
38
Figure Legends
Figure 1 Mean (±SE) upstream passage efficiency for all orders of fishes with N≥5.
Entire community refers to studies that measured the entire non-salmonid community
with no distinction between orders. In all figures, numerals above the bars represent
sample sizes.
Figure 2 Mean (±SE) passage efficiencies for up- and downstream migration at fish
passage facilities for salmonid and non-salmonid fishes in North America, Europe, and
South America/Australia.
Figure 3 Mean (±SE) upstream passage efficiency for migration at five types of fish
passage facility, for salmonid and non-salmonid fishes.
Figure 4 Upstream passage efficiency, for salmonid and non-salmonid fishes in relation
to a) fishway slope, b) fishway length, c) water velocity through the fishway, and d) total
fish length. Lines represent least-squares regressions.
Figure 5 Mean (±SE) percentage of fish that fell back at fishways, defined as the
percentage of fish that passed back downstream via spillways or turbine intakes, after the
successful ascension of a fishway, for four different species of salmonids. SP-SU chinook
are spring-summer running chinook, fall chinook are fall running chinook.
Figure 6 Upstream attraction and entrance efficiencies in relation to a) fishway slope and
b) fishway length for all fish species. Lines represent least-squares regressions.
39
Figure 1:
40
Figure 2:
41
Figure 3:
42
Figure 4:
43
Figure 5:
44
Figure 6:
45